Sea buckthorn (SB) seeds were used as raw material to obtain SB oil using two extraction methods: ultrasound and microwave assisted extraction. The favorable experimental conditions that maximize the extraction efficiency were investigated by applying response surface methodology (RSM). The selected key independent variables were ultrasonic intensity (UI), temperature, and time for ultrasound assisted extraction (UAE) and microwave power, time, and solid/liquid ratio for microwave assisted extraction (MAE). The results obtained for extraction efficiency under optimal conditions are comparable for the two extraction methods (89.2 ± 0.50% for MAE and 87.4 ± 0.44% for UAE). The operation conditions for maximum extraction efficiency were: 13.77 W/cm2 UI, 40 °C temperature, and 10 min extraction time for UAE and 225 W microwave power, 15 ml/ g solid/liquid ratio, and 20 min extraction time for MAE. The extraction kinetics was characterized using a second order model for optimal conditions for UAE and MAE of SB seed oil. Practical applications This article describes two modern methods of sea buckthorn seed oil extraction: ultrasound assisted extraction (UAE) and microwave assisted extraction. Both methods offer many advantages if they are likened with conventional oil extraction. The results illustrated that both methods give comparable values for extraction efficiency, but with an advantage for UAE. The extraction time for UAE is shorter in comparison with MAE (10 min in comparison with 20 min).

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This paper’s aim was to model the adsorption of VOC (volatile organic compound) vapor from gas streams onto fixed bed porous adsorbent particles under various operation conditions. A mathematical model based on gas plug flow was developed to predict the process dynamics. An experimental study to highlight the influence of process variables on adsorption dynamics, described by bed saturation curves, was performed in order to identify the more relevant model parameters for the laboratory scale fixed bed adsorption column used. Experimental data concerning the adsorption of n-hexane and 2-propanol from air streams onto fixed bed granular activated carbon emphasized an increase in saturation adsorption capacity of activated carbon at high values of operation temperature and species boiling point as well as at a low level of air superficial velocity. The model predicted well the real conditions, and it could facilitate the design, scale-up, and operation of fixed bed adsorption columns.

A new method for synthesis of carbon-supported catalysts where precursors were obtained by slow pyrolysis of whole (8 mm) and ground (4 and 2 mm) corn grains impregnated with nickel nitrate solution is described. Carbon-supported nickel catalysts prepared by precursor activation at three levels of maximum activation temperature (600, 680, and 750 °C) were characterized and tested in the liquid-phase cinnamaldehyde hydrogenation. The influence of corn grain size and maximum activation temperature on catalyst texture, nickel loading, nickel nanoparticle size, and hydrogenation reaction performances was evaluated. An increase in BET specific surface (92–379 m2/g), porosity (0.13–0.60), mean pore diameter (12.8–22 nm), nickel loading (3.56–25.41%), and nickel nanoparticle size (21–55 nm) was found with decreasing grain size and increasing activation temperature. The highest values of cinnamaldehyde conversion (97%) and initial turnover frequency (0.31 and 0.36 s–1) were obtained for supported catalysts prepared from ground grains activated at 750 °C.

Three groups of Romanian acacia honey, i.e., pure, directly adulterated (by mixing the pure honey with three sugar syrups), and indirectly adulterated (by feeding the bees with the same syrups), were characterized and discriminated based on their physicochemical parameters. Moisture, ash, 5-hydroxymethylfurfural (HMF), reducing sugars (fructose and glucose), and sucrose contents, free acidity, diastase activity, ratio between stable carbon isotopes of honey and its proteins (δ13CH and δ13CP) were evaluated. Adulteration led to a significant increase in sucrose content, HMF level, and Δδ13C = δ13CH‒δ13CP as well a decrease in reducing sugar content and diastase activity. Principal component analysis (PCA) and linear discriminant analysis (LDA) were applied to experimental data in order to distinguish between pure and adulterated honey. The most relevant discriminative parameters were diastase activity, HMF, sucrose, and reducing sugar contents. Posterior classification probabilities and classification functions obtained by LDA revealed that 100% of honey samples were correctly assigned to their original group.